Software Alternatives & Startups

WebPlotDigitizer VS DataMelt

Compare WebPlotDigitizer VS DataMelt and see what are their differences

WebPlotDigitizer

WebPlotDigitizer - Web based tool to extract numerical data from plots, images and maps.

Rating
0 reviews
Pricing
Open source
DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.

Rating
5.0 ยท 1 review
Pricing
Open source Freemium Free trial

Which is more popular?

Data Extraction popularity
100% vs 0%
alternatives listed
16 vs 44

Base details

Website, pricing, platforms and company facts side by side.

WPD
WebPlotDigitizer
DataMelt
Website automeris.io datamelt.org
Pricing
Open source
Open source Freemium Free trial
Platforms โ€”
Linux Windows Mac OSX Java Cross Platform +2
Company โ€” 2020
Listed in

About WebPlotDigitizer and DataMelt

In their own words, as submitted to SaaSHub.

WPD
WebPlotDigitizer
DataMelt

No description of WebPlotDigitizer yet.

DataMelt is a Java program for statistics, general data analysis and data visualization. The program is often termed "computational platform" since it can be used with different programming languages (Java, Python, Groovy..). DataMelt is not limited to a single programming language. The program...

Read more about DataMelt

Features and specs

What each product offers, as listed by its team.

WPD
WebPlotDigitizer 5 features
DataMelt 5 features
  • User-Friendly Interface
    WebPlotDigitizer offers an intuitive, easy-to-navigate interface, making it accessible for users without extensive technical expertise.
  • Cross-Platform Capability
    Being a web-based tool, WebPlotDigitizer works across various operating systems such as Windows, macOS, and Linux without requiring installation.
  • Supports Multiple Plot Types
    The tool can digitize diverse chart types, including line plots, bar charts, scatter plots, and heat maps, enhancing its versatility.
  • Free to Use
    WebPlotDigitizer provides its core features without cost, making it accessible to a wide user base, including students and researchers.
  • Batch Processing
    The tool allows for batch processing of multiple images, saving time and effort when dealing with large datasets.

Possible disadvantages

  • Accuracy Concerns
    The accuracy of digitized data can vary based on the quality of the input image and user interaction, which may require manual adjustments.
  • Limited Advanced Features
    While suitable for basic digitization tasks, WebPlotDigitizer lacks some advanced features and customization options found in dedicated data analysis software.
  • Dependency on Internet Connection
    As a web-based tool, WebPlotDigitizer requires an internet connection, which can be a limitation for offline work.
  • Learning Curve
    Some users may experience a learning curve with initial usage, especially when dealing with more complex digitization tasks.
  • Versatility
    DataMelt supports a wide range of programming languages including Java, Jython, Groovy, and JRuby, making it versatile for users familiar with different coding environments.
  • Rich Libraries
    It offers a comprehensive set of scientific libraries for numerical computation, data analysis, and visualization, which can be beneficial for complex scientific research and data processing tasks.
  • Cross-Platform
    DataMelt is platform-independent, running on any operating system that supports Java, such as Windows, macOS, and Linux. This makes it accessible to a wide audience.
  • Integrated Development Environment
    DataMelt provides a powerful IDE that integrates coding, plotting, and visualization tools, streamlining the workflow for developers and researchers.
  • Free and Open Source
    The core functionality of DataMelt is available for free, which can be appealing to individuals and organizations looking for budget-friendly computational tools.

Analysis

An editorial look at what each product does well and who it suits.

WPD
WebPlotDigitizer
DataMelt

Overall verdict

  • Overall, WebPlotDigitizer is a robust and effective tool for converting graphical data into numerical form. Its combination of ease of use and powerful features makes it a reliable choice for those needing to extract data from images.

Why this product is good

  • WebPlotDigitizer is considered a good tool because it provides users with the ability to extract numerical data from various types of plots, images, and charts efficiently. Its features, such as auto-extraction, color channel selection, and curve fitting, make it versatile for different kinds of data extraction tasks. The tool is also web-based, meaning users can access it easily without needing to install software on their local machines. Additionally, it supports multiple file formats and offers a straightforward user interface, contributing to its popularity in academic and professional settings.

Recommended for

    WebPlotDigitizer is recommended for researchers, scientists, data analysts, and students who frequently need to extract data from published graphs and charts. It is particularly useful in fields such as biology, engineering, physics, and any other areas where visual data needs to be quantitatively analyzed.

No analysis of DataMelt yet.

Videos

Walkthroughs and reviews on video.

WPD
WebPlotDigitizer 2 videos + Add
DataMelt 0 videos + Add

๐Ÿ”ด Webplotdigitizer Tutorial - A Plot Digitizer to Digitize Graphs

More videos

  • - WebPlotDigitizer v2.5 Tutorial - 2D XY plots and general tips.

No DataMelt videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0โ€“100% relative to the other.

Score bands 0โ€“20 21โ€“40 41โ€“50 51โ€“60 61โ€“100
WPD
WebPlotDigitizer
DataMelt
100% 100%
0% 0%
0% 0%
100% 100%
100% 100%
0% 0%
0% 0%
100% 100%

Questions & Answers

As answered by people managing WebPlotDigitizer and DataMelt.

How would you describe the primary audience of your product?

DataMelt's answer:

students and data scientists

What's the story behind your product?

DataMelt's answer:

DataMelt has its roots in particle physics where data mining is a primary task. It was created as Software:jHepWork project in 2005 and it was initially written for data analysis for particle physics.

What makes your product unique?

DataMelt's answer:

Multiplatform. Supports multiple programming languages: Java, Python (Jython), Groovy, Ruby

Why should a person choose your product over its competitors?

DataMelt's answer:

Large database of examples and code snippets https://datamelt.org/code/

Who are some of the biggest customers of your product?

DataMelt's answer:

Students at universities and data scientists.

Which are the primary technologies used for building your product?

DataMelt's answer:

Java (JDK any new new release including JDK20)

User comments

Share your experience with using WebPlotDigitizer and DataMelt. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

WPD
WebPlotDigitizer no reviews yet
DataMelt 5.0 ยท 1 review

We have no reviews of WebPlotDigitizer yet. Be the first one to post

  • Great 3D graphics
    SaaSHub review
    ยท Dec 2019

    I like this DataMelt analysis program since it has many 2D/3D visualisation and a massive number of practical examples

Alternatives to WebPlotDigitizer and DataMelt

When comparing WebPlotDigitizer and DataMelt, you can also consider the following products.